Measuring interfraction and intrafraction lung function changes during radiation therapy using four‐dimensional cone beam CT ventilation imaging

Kipritidis, John; Hugo, Geoffrey D.; Weiss, Elisabeth; Williamson, Jeffrey F.; Keall, Paul J.

doi:10.1118/1.4907991

Cited by 37 publications

(44 citation statements)

References 37 publications

(43 reference statements)

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“…Ventilation differences introduced by registration errors can be reduced by smoothing. This evaluation study and previous reports 15 , 18 support the use of ventilation calculated using 4D CT in clinical applications such as radiation treatment planning, 12 , 23 , 24 , 40 , 42 , 43 , 44 , 45 pulmonary function, 15 , 18 and lung disease (22) …”

Section: Discussionsupporting

confidence: 79%

“…For example, 4D CT‐based ventilation has been used in radiation therapy treatment planning to avoid functional lung and to estimate loss of lung function or normal tissue toxicity after radiotherapy in a dose‐dependent manner 40 , 42 , 43 , 44 , 45 . Additional medical applications, such as in diagnostic imaging, may be possible.…”

Section: Discussionmentioning

confidence: 99%

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Evaluation of the ΔV 4D CT ventilation calculation method usingin vivoxenon CT ventilation data and comparison to other methods

Zhang

Latifi

et al. 2016

J Applied Clin Med Phys

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Ventilation distribution calculation using 4D CT has shown promising potential in several clinical applications. This study evaluated the direct geometric ventilation calculation method, namely the ΔV method, with xenon‐enhanced CT (XeCT) ventilation data from four sheep, and compared it with two other published methods, the Jacobian and the Hounsfield unit (HU) methods. Spearman correlation coefficient (SCC) and Dice similarity coefficient (DSC) were used for the evaluation and comparison. The average SCC with one standard deviation was 0.44±0.13 with a range between 0.29 and 0.61 between the XeCT and DLV ventilation distributions. The average DSC value for lower 30% ventilation volumes between the XeCT and ΔV ventilation distributions was 0.55±0.07 with a range between 0.48 and 0.63. Ventilation difference introduced by deformable image registration errors improved with smoothing. In conclusion, ventilation distributions generated using ΔV‐4D CT and deformable image registration are in reasonably agreement with the in vivo XeCT measured ventilation distribution.PACS number(s): 87.57.N‐, 87.57.nj, 87.57.Q‐, 87.85.Pq

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Section: Discussionsupporting

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Evaluation of the ΔV 4D CT ventilation calculation method usingin vivoxenon CT ventilation data and comparison to other methods

Zhang

Latifi

et al. 2016

J Applied Clin Med Phys

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“…Recently, the time synchronized CBCT (4DCBCT) method has been introduced to manage respiration-induced target motion during treatment verification imaging. [22][23][24][25][26][27][28][29][30] In 4DCBCT imaging, two-dimensional (2D) projections acquired at different times and positions are sorted into several groups, according to their respiratory phases, and each phase group is then reconstructed independently to obtain a volumetric image corresponding to that specific phase. The respiratory wave required for retrospective 4DCBCT reconstructions is derived using either 2D projections of CBCT itself or an external surrogate system.…”

mentioning

confidence: 99%

Evaluating the four-dimensional cone beam computed tomography with varying gantry rotation speed

Yoganathan¹,

Das²,

Ali³

et al. 2016

BJR

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“…2. In order to facilitate a 4DCT‐ventilation comparison at different time points, the 4DCT‐ventilation images were registered (using MIM Vista Version 6.7 [Cleveland, OH]) and normalized 12, 13, 14…”

Section: Methodsmentioning

confidence: 99%

Using 4DCT‐ventilation to characterize lung function changes for pediatric patients getting thoracic radiotherapy

Vinogradskiy

Faught

Castillo

et al. 2018

J Applied Clin Med Phys

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PurposeA form of lung functional imaging has been developed that uses 4DCT data to calculate ventilation (4DCT‐ventilation). Because 4DCTs are acquired as standard‐of‐care to manage breathing motion during radiotherapy, 4DCT‐ventilation provides functional information at no extra dosimetric or monetary cost. 4DCT‐ventilation has yet to be described in children. 4DCT‐ventilation can be used as a tool to help assess post‐treatment lung function and predict for future clinical thoracic toxicities for pediatric patients receiving radiotherapy to the chest. The purpose of this work was to perform a preliminary evaluation of 4DCT‐ventilation‐based lung function changes for pediatric patients receiving radiotherapy to the lungs.MethodsThe study used four patients with pre and postradiotherapy 4DCTs. The 4DCTs, deformable image registration, and a density‐change‐based algorithm were used to compute pre and post‐treatment 4DCT‐ventilation images. The post‐treatment 4DCT‐ventilation images were compared to the pretreatment 4DCT‐ventilation images for a global lung response and for an intrapatient dose–response (providing an assessment for dose‐dependent regional dose–response).ResultsFor three of the four patients, a global ventilation decline of 7–37% was observed, while one patient did not demonstrate a global functional decline. Dose–response analysis did not reveal an intrapatient dose–response from 0 to 20 Gy for three patients while one patient demonstrated increased 4DCT‐ventilation decline as a function of increasing lung doses up to 50 Gy.ConclusionsCompared to adults, pediatric patients have unique lung function, dosimetric, and toxicity profiles. The presented work is the first to evaluate spatial lung function changes in pediatric patients using 4DCT‐ventilation and showed lung function changes for three of the four patients. The early changes demonstrated with lung function imaging warrant further longitudinal work to determine whether the imaging‐based early changes can be predicted for long‐term clinical toxicity.

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Measuring interfraction and intrafraction lung function changes during radiation therapy using four‐dimensional cone beam CT ventilation imaging

Cited by 37 publications

References 37 publications

Evaluation of the ΔV 4D CT ventilation calculation method usingin vivoxenon CT ventilation data and comparison to other methods

Evaluation of the ΔV 4D CT ventilation calculation method usingin vivoxenon CT ventilation data and comparison to other methods

Evaluating the four-dimensional cone beam computed tomography with varying gantry rotation speed

Using 4DCT‐ventilation to characterize lung function changes for pediatric patients getting thoracic radiotherapy

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